摘要:In this paper, we describe how the pathfinder algorithm converts relatednessratings of concept pairs to concept maps; we also present howthis algorithm has been used to develop the Concept Maps for Learningwebsite (www.conceptmapsforlearning.com) based on the principles of effectiveformative assessment. The pathfinder networks, one of the networkrepresentation tools, claim to help more students memorize and recall therelations between concepts than spatial representation tools (such as Multi-Dimensional Scaling). Therefore, the pathfinder networks have been usedin various studies on knowledge structures, including identifying students’misconceptions. To accomplish this, each student’s knowledge map and theexpert knowledge map are compared via the pathfinder software, and thedifferences between these maps are highlighted. After misconceptions areidentified, the pathfinder software fails to provide any feedback on thesemisconceptions. To overcome this weakness, we have been developing amobile-based concept mapping tool providing visual, textual and remedialfeedback (ex. videos, website links and applets) on the concept relations.This information is then placed on the expert concept map, but not on thestudent’s concept map. Additionally, students are asked to note what theyunderstand from given feedback, and given the opportunity to revise theirknowledge maps after receiving various types of feedback.